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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Edutech Semantik Techno.Com: Jurnal Teknologi Informasi Bulletin of Electrical Engineering and Informatics JSI: Jurnal Sistem Informasi (E-Journal) Jurnal Ilmiah Kursor Jurnal Transformatika International Journal of Advances in Intelligent Informatics Scientific Journal of Informatics JAIS (Journal of Applied Intelligent System) JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Tech-E Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control CogITo Smart Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING International Journal of New Media Technology MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Data Science: Journal of Computing and Applied Informatics JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Building of Informatics, Technology and Science Indonesian Journal of Electrical Engineering and Computer Science Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences JOURNAL SCIENTIFIC OF MANDALIKA (JSM) Jurnal Pendidikan dan Teknologi Indonesia Jurnal Teknologi Informasi Cyberku Studies in English Language and Education Moneter : Jurnal Keuangan dan Perbankan Scientific Journal of Informatics Journal on Pustaka Cendekia Informatika
Pulung Nurtantio Andono
Universitas Dian Nuswantoro
Aerospace Engineering Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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Optimized Visualization of Digital Image Steganography using Least Significant Bits and AES for Secret Key Encryption Jatmoko, Cahaya; Sinaga, Daurat; Lestiawan, Heru; Astuti, Erna Zuni; Sari, Christy Atika; Shidik, Guruh Fajar; Andono, Pulung Nurtantio; Yaacob, Noorayisahbe Mohd
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 10, No. 3, August 2025
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v10i3.2252

Abstract

Data hiding is a technique used to embed secret information into a cover medium, such as an image, audio, or video, with minimal distortion, ensuring that the hidden data remains imperceptible to an observer. The key challenge lies in embedding secret information securely while maintaining the original quality of the host medium. In image-based data hiding, this often means ensuring the hidden data cannot be easily detected or extracted while still preserving the visual integrity of the host image. To overcome this, we propose a combination of AES (Advanced Encryption Standard) encryption and Least Significant Bit (LSB) steganography. AES encryption is used to protect the secret images, while the LSB technique is applied to embed the encrypted images into the host images, ensuring secure data transfer. The dataset includes grayscale 256x256 images, specifically "aerial.jpg," "airplane.jpg," and "boat.jpg" as host images, and "Secret1," "Secret2," and "Secret3" as the encrypted secret images. Evaluation metrics such as Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), Unified Average Changing Intensity (UACI), and Number of Pixels Changed Rate (NPCR) were used to assess both the image quality and security of the stego images. The results showed low MSE (0.0012 to 0.0013), high PSNR (58 dB), and consistent UACI and NPCR values, confirming both the preservation of image quality and the effectiveness of encryption for securing the secret data.
Enhancing challenge-based immersion in cultural game using appreciative fuzzy logic Muljono, Muljono; Haryanto, Hanny; Andono, Pulung Nurtantio; Nugroho, Raden Arief; Yakub, Fitri; Sukmono, Indriyo K.
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i5.pp3702-3714

Abstract

Many traditional games in Indonesia are considered cultural heritage and are in serious decline; young generations no longer know about them. Serious games have been considered a potential educational tool for cultural heritage preservation. Lack of immersive experience due to over-focus on the learning content is a common problem in those games. Very little research also discusses cultural heritage serious game design frameworks. This study uses the appreciative fuzzy logic system (AFLS) to enhance the challenge-based immersive experience (CBIE) in the Joglosemar cultural heritage game. The AFLS provides autonomous challenges, such as enemy numbers and aggressive behavior, and the frequency of item appearances in the games using fuzzy logic with respect to the appreciative serious games (ASG) concepts. The ASG is the design guide for serious games that divides the game activities into 4-D: discovery, dream, design, and destiny. We use three ASG-based serious games to evaluate the CBIE produced by AFLS. The game experience questionnaire (GEQ) is used to measure the player experience, while the cross-validation is used to measure the AFLS performance. Results show that the AFLS enhances the CBIE. The study contributes mainly to provide reliable intelligent system for automated serious game design.
Hyperparameter Tuning with Optuna to optimize the YOLOv11n Model for Weed Detection Candhy Fadhila Arsyad; Pulung Nurtantio Andono; Moch Arief Soeleman
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 5 (2025): October 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i5.6682

Abstract

Accurate weed detection is essential for maintaining the cleanliness and aesthetic appeal of residential yards. This study aimed to optimize YOLOv11n, a lightweight object detection model, to achieve high precision in weed identification under real-world conditions. The novelty of this study lies in the application of Optuna, an automatic hyperparameter optimization framework, to enhance model performance while maintaining computational efficiency for resource-limited devices such as drones and IoT systems. The research involved data augmentation techniques including crop (0–20% zoom), hue (±20°), saturation (±30%), brightness (±20%), exposure (±15%), and mosaic augmentation. These augmented images were used to train four YOLO nano variants (v5n, v8n, v11n, v12n), which were evaluated using standard metrics: Precision, Recall, F1-Score, and mean Average Precision (mAP). Among the models tested, YOLOv11n with Custom Optuna configuration delivered the highest performance, achieving a 94.6% F1-score and 97.8% mAP@0.5. These results demonstrate that the optimized YOLOv11n model can support accurate and efficient real-time weed detection in household environments, particularly on edge devices with limited hardware capabilities. This makes it a viable solution for practical implementation in precision agriculture and smart gardening.
Evaluating the Impact of Particle Swarm Optimization Based Feature Selection on Support Vector Machine Performance in Coral Reef Health Classification Bastiaans, Jessica Carmelita; Hartojo, James; Pramunendar, Ricardus Anggi; Andono, Pulung Nurtantio
IJNMT (International Journal of New Media Technology) Vol 11 No 2 (2024): Vol 11 No 2 (2024): IJNMT (International Journal of New Media Technology)
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v11i2.3761

Abstract

This research explores improving coral reef image classification accuracy by combining Histogram of Oriented Gradients (HOG) feature extraction, image classification with Support Vector Machine (SVM), and feature selection with Particle Swarm Optimization (PSO). Given the ecological importance of coral reefs and the threats they face, accurate classification of coral reef health is essential for conservation efforts. This study used healthy, whitish, and dead coral reef datasets divided into training, validation, and test data. The proposed approach successfully improved the classification accuracy significantly, reaching 85.44% with the SVM model optimized by PSO, compared to 79.11% in the original SVM model. PSO not only improves accuracy but also reduces running time, demonstrating its effectiveness and computational efficiency. The results of this study highlight the potential of PSO in optimizing machine learning models, especially in complex image classification tasks. While the results obtained are promising, the study acknowledges several limitations, including the need for further validation with larger and more diverse datasets to ensure model robustness and generalizability. This research contributes to the field of marine ecology by providing a more accurate and efficient coral reef classification method, which can be applied to other image classifications.
Enhancing Support Vector Machine Classification of Nutrient Deficiency in Rice Plants Through Particle Swarm Optimization-Based Feature Selection Hartojo, James; Bastiaans, Jessica Carmelita; Pramunendar, Ricardus Anggi; Andono, Pulung Nurtantio
IJNMT (International Journal of New Media Technology) Vol 11 No 2 (2024): Vol 11 No 2 (2024): IJNMT (International Journal of New Media Technology)
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v11i2.3762

Abstract

The research focuses on the classification of nutrient deficiencies in rice plant leaves using a combination of Support Vector Machine (SVM) and Particle Swarm Optimization (PSO) methods for feature selection. Image features are extracted using Histogram of Oriented Gradients (HOG), which is then optimized with PSO to select the most relevant features in the classification process. Indonesia is one of the largest rice producers in the world, with food security as a major issue that requires sustainable solutions, especially in the agricultural sector. The growth and yield of rice plants are highly dependent on the availability of nutrients such as Nitrogen (N), Phosphorus (P), and Potassium (K). However, traditional observation methods to detect nutrient deficiencies in plants become inefficient as the scale of production increases. The dataset used includes images of rice leaves showing nitrogen (N), phosphorus (P), and potassium (K) deficiencies. Experiments show that the SVM model optimized with PSO provides a classification accuracy of 83.19% and a runtime of 129.63 seconds with 1150 best feature combinations out of 2303 extracted features, which is higher accuracy and faster runtime than the model that does not use PSO. These results show that the integration of PSO in the feature selection process not only improves the accuracy of the model, but also reduces the required computation time. This research makes an important contribution to the development of an automated system for the classification of nutrient deficiencies in crops, which can be implemented in large farms or other agricultural fields.
IMPLEMENTATION OF LSTM (LONG SHORT TERM MEMORY) ALGORITHM TO PREDICT WEATHER IN CENTRAL JAVA Irwan, Rhedy; Andono, Pulung Nurtantio; Al Zami, Farrikh; Ocky Saputra, Filmada; Megantara, Rama Aria; Handoko, L. Budi; Umam, Chaerul
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 6 (2023): JUTIF Volume 4, Number 6, Desember 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.6.1118

Abstract

Agro-indutrial agricultural production such as red onions in Indonesia has a very important share in driving Indonesia's economic growth, especially in Central Java province which contributed 28.15% of the total national red onion production in 2021. Weather conditions have a major influence on the red onion planting process until the red onions are ready to be harvested. In this study, the objective is to predict various types of weather such as rainfall, air temperature, and air humidity in seven districts in Central Java, namely Brebes, Temanggung, Demak, Boyolali, Kendal, Pati, and Tegal. To do this, the use of the LSTM (Long Short Term Memory) algorithm with its ability to store memory longer than RNN will be reliable for predicting various types of weather in the future. This research was developed with the CRISP-DM (Cross Industry Process Model for Data Mining) method which has a goal-oriented approach, this method is a mature and widely accepted method in Data Mining with various applications in Machine Learning. With the final results from 39 models by using the evaluation of the average value of train MSE 0.013, test RMSE 0.11, test MSE of 0.02, test RMSE 0.12 and succeed to predict 5 days or months ahead from the last data that is provided.
Imperceptible Watermarking Using Discrete Wavelet Transform and Daisy Descriptor for Hiding Noisy Watermark Abdussalam, Abdussalam; Umam, Chaerul; Sari, Wellia Shinta; Rachmawanto, Eko Hari; Shidik, Guruh Fajar; Andono, Pulung Nurtantio; Lestiawan, Heru; Islam, Hussain Md Mehedul
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 2 (2025): JUTIF Volume 6, Number 2, April 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.2.4423

Abstract

This research aims at overcoming the challenge of improving security and robustness in digital image watermarking, a critical activity in protecting intellectual property against misuse and manipulation. In a move to overcome such a challenge, this work introduces a new form of watermarking that incorporates Discrete Wavelet Transform (DWT) and Daisy Descriptor, with a view to enhancing both durability and invisibility of the watermark. The proposed method embeds a noise-variant watermark into selected frequency sub-bands using DWT, while the Daisy Descriptor enhances resistance to noise-based attacks. Testing conducted with three grayscale images, namely Lena, Cameraman, and Lion, each with a resolution of 512 × 512 pixels, showed that the proposed DWT-Daisy Descriptor outperforms current methodologies, producing high Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) values. In fact, in Lena, a PSNR value of 63.71 dB and an SSIM value of 1 were attained, with Cameraman having a PSNR value of 68.33 dB and an SSIM value of 1. As for attack resistivity, a high PSNR value of 50.11 dB under Gaussian attack and 55.70 dB under Salt-and-Pepper attack, with SSIM values approaching 1, confirm the robustness of the proposed scheme. This study highlights the significance of an efficient and secure watermarking technique that not only preserves image quality but also withstands various distortions, making it highly relevant for digital content protection in modern multimedia applications.
Securing Medical Images Using Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) for Image Steganography Pramudya, Elkaf Rahmawan; Handoko, L. Budi; Harjo, Budi; Sani, Ramadhan Rakhmat; Sari, Christy Atika; Shidik, Guruh Fajar; Andono, Pulung Nurtantio; Sarker, Md. Kamruzzaman
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 2 (2025): JUTIF Volume 6, Number 2, April 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.2.4426

Abstract

Steganography is a technique for embedding secret information into digital media, such as medical images, without significantly affecting their visual quality. The primary challenge in medical image steganography is preserving the quality of the cover image while ensuring robustness against distortions such as compression or data manipulation attacks, which may impact diagnostic accuracy. This study proposes an enhanced steganographic method based on Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) to improve the security and robustness of medical image embedding. DWT decomposes the medical image into four frequency sub-bands (LL, LH, HL, HH), while SVD is applied to embed the secret image while maintaining essential medical features. Experimental results show that the proposed method achieves a PSNR value of up to 78 dB and an SSIM value approaching 1, indicating that the stego image quality is nearly identical to the original cover image. Compared to previous DCT-SVD and IWT-SVD-based approaches, the DWT-SVD method offers superior robustness and imperceptibility, particularly in preserving image quality in complex-textured medical images. This method contributes to enhancing data security in telemedicine and AI-based medical imaging applications by ensuring that sensitive medical data remains protected while preserving image integrity for diagnostic use.
Penerapan Metode SAW untuk Perancangan SPK Penerimaan Karyawan Di PT Pinnacle Apparels Novianto, Sendi; Panca Hutama Caniago; Pulung Nurtantio Andono
Journal on Pustaka Cendekia Informatika Vol. 1 No. 2 (2023): Journal on Pustaka Cendekia Informatika: Volume 1 Nomor 2 June-September Tahun
Publisher : PT Pustaka Cendekia Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70292/pctif.v1i2.19

Abstract

A company cannot grow without the support of its employees as one of its pillars. Therefore, the company needs to recruit potential and talented candidates who can contribute to its success. Skilled employees who can help the company grow and compete with the changing times are now receiving special attention, as recruitment processes that do not meet the company's needs can hinder its development. Hence, a decision support system is needed for the employee selection process. This decision support system utilizes the Simple Additive Weighting (SAW) method. Candidates are compared to each other, resulting in a prioritized intensity value that assesses each candidate. This decision support system simplifies the evaluation of each candidate and allows for changes in criteria and weight values. This decision support system is beneficial for facilitating decision-making related to the selection of suitable candidates, ensuring that the company hires the most suitable employees
Strategi Komunikasi Dalam Pelayanan Masyarakat pada Anggota Kepolisian di Polres Klaten Widyatmoko, Karis; Wahyu Mulyono, Ibnu Utomo; Ningrum, Novita Kurnia; Umami, Zahrotul; Andono, Pulung Nurtantio
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 6, No 3 (2023): September 2023
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v6i3.1618

Abstract

Keberadaan suatu organisasi atau institusi memiliki aspek yang perlu dicapai bersama seperti visi misi. Anggota organisasi perlu menyamakan persepsi dan langkah untuk mencapai tujuan bersama. Demikian juga dengan Polres Klaten sebagai institusi kepolisian membutuhkan adanya kesamaan persepsi dan tujuan dalam menjalankan tugas baik dalam internal kepolisian maupun eksternal untuk memberikan informasi dan melayani masyarakat. Untuk menjaga integritas Polres Klaten dalam menjalankan tugas dalam melayani masyarakat dibutuhkan adanya pengelolaan yang efektif baik sehingga visi misi institusi dapat terus dijalankan sehingga tujuan bersamaa intitusi dapat diwujudkan. Salah satu hal penting dalam pengelolaan institusi adalah bagaiamana komunikasi dapat dijalankan secara baik, informasi dapat tersampaikan dengan utuh pada seluruh anggota polisi di Polres Klaten. Oleh karena itu dibutuhkan adanya strategi komunikasi yang tepat agar masalah yang disebabkann adanya penyampaian informasi yang buruk dapat diminimalisir. Dengan menerapkan strategi komunikasi yang tepat diharapkan Polres Klaten diharapkan dapat mengantisipasi konflik internal anggota maupun eksternal dalam melayani masyarakat. Dengan demikian fungsi dan tugas dari masing masing lapisan jabatan dapat terlaksana dengan baik sehingga tujuan bersama di Polres Klaten dapat tercapai.
Co-Authors Abdussalam Abdussalam, Abdussalam Achmad Ridwan Affandy Agus Winarno, Agus Al zami, Farrikh Al-Fatih, Gilang Fajar Alzami, Farrikh Aria Hendrawan, Aria Arry Maulana Syarif, Arry Maulana Asih Rohmani Asih Rohmani, Asih Bastiaans, Jessica Carmelita Budi Harjo Cahaya Jatmoko Candhy Fadhila Arsyad Catur Supriyanto Catur Supriyanto Catur Supriyanto Catur Supriyanto Catur Supriyanto Catur Supriyanto Chaerul Umam Christy Atika Sari D, Ishak Bintang Dalimarta, Fahmy Ferdian Danang Bagus Chandra Prasetiyo Darmawan, Aditya Aqil Denny Senata Dito, Aliffia Putri Doheir, Mohamed Dwi Eko Waluyo Dwi Puji Prabowo, Dwi Puji Dwiza Riana Edi Noersasongko Edi Noersasongko Edi Noersasongko Egia Rosi Subhiyakto, Egia Rosi Ekaprana Wijaya Eko Hari Rachmawanto Elkaf Rahmawan Pramudya Erna Zuni Astuti Fajrian Nur Adnan Fauzi Adi Rafrastara Firman Wahyudi, Firman Fitri Yakub Guruh Fajar Shidik Hamir, Mun Hanny Haryanto Hartojo, James Harun Al Azies Heru Lestiawan Hidayat, Sholeh Hisyam Syarif Husain Husain I Ketut Eddy Purnama Ibnu Utomo Wahyu Mulyono, Ibnu Utomo Irwan, Rhedy Islam, Hussain Md Mehedul Ivan Maulana Jumanto Jumanto, Jumanto Junta Zeniarja Karis Widyatmoko Khafiizh Hastuti Kiat, Ng Poh Kunio Kondo L. Budi Handoko M Arief Soeleman M. Arief Soeleman M. Arif Soeleman Maria Goretti Catur Yuantari Megantara, Rama Aria Mila Sartika, Mila Minghat, Asnul Dahar Bin Moch Arief Soeleman Moch Arief Soeleman Moch Arief Soeleman, Moch Arief Mochamad Hariadi Mochammad Arief Soeleman Muhammad Munsarif Muhammad Naufal, Muhammad Muljono Muljono Nanna Suryana Herman Ningrum, Novita Kurnia Nita Merlina Noor Ageng Setiyanto, Noor Ageng Nur Azise Ocky Saputra, Filmada Panca Hutama Caniago Paramita, Cinantya Pergiwati, Dewi Pramitasari, Ratih Prasetyoningrum, Devi Puji Purwatiningsih, Aris Pujiono Pujiono Purwanto Purwanto Putra, Angga Permana Raden Arief Nugroho Rafsanjani, Muhammad Ivan Rahmatullah, Muhammad Rifqi Fadhlan Ramadhan Rakhmat Sani ramayanti, ismarita Ricardus Anggi P Ricardus Anggi Pramunendar Rohman, Muhammad Syaifur Ruri Suko Basuki Saputra, Filmada Ocky Saputri, Pungky Nabella Saputro, Wicaksono Agung Saraswati, Galuh Wilujeng Sari Ayu Wulandari Sarker, Md. Kamruzzaman Satriyawibawa, Muhammad Yiko Savicevic, Anamarija Jurcev Senata, Denny Sendi Novianto Shafa, Raihanaldy Ash Shier Nee Saw Sinaga, Daurat Sindhu Rakasiwi Siti Hadiati Nugraini Soeleman, M Arief Soeleman, M. Arief Soeleman, Moch. Arief Soong, Lim Way Sri Winarno Sri Winarno Steven, Alvin Sudibyo, Usman Sukmawati Anggraeni Putri, Sukmawati Anggraeni Sukmono, Indriyo K. Supriyono Asfawi Susanto Susanto Tendi Tri Wiyanto, Tendi Tri Tengku Riza Zarzani N Thifaal, Nisrina Salwa Torhino, Rizal Wellia Shinta Sari Yaacob, Noorayisahbe Mohd Yusianto Rindra Zahrotul Umami, Zahrotul Zainal Arifin Hasibuan